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Development of a collision-avoidance vector based control algorithm for automated in-vivo transportation of biological cells

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

With the rapid development of precision medicine, the in-vivo manipulation of microparticles has attracted increased attention in recent years. Collision is a main cause of the failure of in-vivo particle transportation. In this paper, an automated control approach with obstacle avoidance function is proposed for in-vivo cell transportation. In the proposed approach, a collision-avoidance vector method is utilized to avoid obstacles during the transportation of the target cell. The proposed method integrates obstacle detection and collision avoidance into a single step, hence reducing the duration of online processing while enhancing the accuracy of obstacle detection. With the proposed approach, different collision avoidance strategies are designed to suit for different transportation environments. The proposed approach exhibits the advantages of reduced online calculation, fast response, high accuracy, and disturbance compensation. Experiments are performed to demonstrate the effectiveness of the proposed controller.
Original languageEnglish
Pages (from-to)147-156
JournalAutomatica
Volume90
Online published15 Feb 2018
DOIs
Publication statusPublished - Apr 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • Closed-loop control
  • Collision avoidance
  • Disturbance compensation
  • In-vivo cell manipulation
  • Optical tweezers

RGC Funding Information

  • RGC-funded

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